Mathematics for Machine Learning

Format: PDF eTextbooks

ISBN-13: 978-1108455145

ISBN-10: 110845514X

Delivery: Instant Download

Authors: Marc Peter Deisenroth

Publisher: Cambridge University Press

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis.

## Reviews

There are no reviews yet.